FP395SCLEROSTIN AND DKK-1 ARE ASSOCIATED WITH MEASURED GFR AND DISEASE BIOMARKERS IN CKD-MBD
Bibliographic record
Abstract
INTRODUCTION AND AIMS: Perturbations to the Wnt/β-Catenin signaling pathway have been implicated in the development of low bone turnover in early stage CKD. Molecules central to this pathway include sclerostin and Dickkopf related protein 1 (DKK-1). The sensitivity and specificity of parathyroid hormone (PTH) for predicting bone turnover is limited, but the ratio of PTH to sclerostin may provide greater utility. This study characterized the levels of sclerostin, DKK-1 and other commonly measured biomarkers across a spectrum of kidney function. METHODS: GFR was measured by inulin clearance (mGFR) in 90 participants. Blood samples were obtained for measurement of sclerostin, DKK-1, fibroblast growth factor 23 (FGF-23), PTH, calcium, phosphate, α-klotho and vitamin D metabolome profiles including 25 hydroxyvitamin D, 1,25-dihydroxyvitamin D, 24,25-dihydroxyvitamin D, and 1,24,25-Trihydroxyvitamin D. Correlation and regression was used to examine the associations between measured values. RESULTS: Mean (SD) age was 60.8 (14.0) yrs and mean mGFR was 44.9 ml/min (range 9.0 to 148.5). Sclerostin increased (r=-0.4, p<0.001) and DKK-1 decreased (r=0.6, p<0.001) as kidney function declined and both associated with phosphate, PTH, FGF-23 and 1,25(OH)2D3 in the unadjusted analysis. In the multi-variable analysis, sclerostin remained significantly associated with FGF-23 after adjustment for mGFR, age and BMI. After adjustment for mGFR, DKK-1 remained significantly associated with FGF-23, PTH, and 24,25(OH)2D3. Study participants were characterized by mGFR according to PTH and sclerostin levels above or below the median (Figure 1). mGFR was significantly higher in the low PTH/low sclerostin group (p<0.0001) and low PTH/high sclerostin group (p<0.05) compared to the high PTH/high sclerostin group. CONCLUSIONS: Sclerostin levels increased and DKK-1 levels decreased as GFR declined and both biomarkers were significantly associated with other parameters of mineral metabolism. GFR significantly influenced the ratio between sclerostin and PTH. Future studies should determine whether the ratio between PTH and wnt signaling inhibitors may be useful in predicting bone histomorphometric findings in patients with CKD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".